Wireless body area networks (BANs) are attracting much attention due to their suitable for healthcare and medical applications. Unfortunately, electrostatic discharge (ESD) is a major electromagnetic (EM) noise source that can degrade wireless communication performance. In this study, we measure EM noise power in the 2.4GHz and 30MHz bands for indirect ESD testing specified in IEC 61000-4-2 standard, and derived a statistical ESD noise model from the measurement results. The ESD noise power was found to follow a lognormal distribution in both 2.4GHz and 30MHz bands. We use this ESD noise model to conduct bit error rate (BER) simulations in a communication channel with additive white Gaussian noise (AWGN) plus ESD noise at 2.4GHz and 30MHz bands. The result is that the BER performance is virtually the same in both bands, and decreases with the signal to noise power ratio (SNR). It is also shown that an error floor exists in the BER performances at both frequencies, which, if the ESD noise power is larger than the Gaussian noise, cannot be improved by increasing the SNR. Although the ESD noise power at 2.4GHz band is nearly 30dB smaller than that at 30MHz band, the signal attenuation along the human body at 2.4GHz band is much larger compared to 30MHz band. This may yield a similar SNR level at 30MHz and 2.4GHz bands in an ESD-dominated environment, so that the 2.4GHz band does not have an obvious merit for BAN applications. Since there are so many in-band interference sources at 2.4GHz band, the 30MHz band seems more promising for vital data transmission in a BAN scenario even in an ESD-dominated environment.

Channel modeling is a vital step in designing transceivers for wireless implant communication systems due to the extremely challenging environment of the human body. In this paper, the in-to-on body path loss and group delay were first analyzed using an electric dipole and a current loop in the 10-60MHz human body communication band. A path loss model was derived using finite difference time domain (FDTD) simulation and an anatomical human body model. As a result, it was found that the path loss increases with distance in an exponent of 5.6 for dipole and 3.9 for loop, and the group delay variation is within 1ns for both dipole and loop which suggests a flat phase response. Moreover, the electric and magnetic field distributions revealed that the magnetic field components dominate in-body signal transmission in this frequency band. Based on the analysis results of the implant channel, the link budget was analyzed. An experiment on a prototype transceiver was also performed to validate the path loss model and bit error rate (BER) performance. The experimentally derived path loss exponent was between the electric dipole path loss exponent and the current loop path loss exponent, and the BER measurement showed the feasibility of 20Mbps implant communication up to a body depth of at least 15cm.

Stimulus response caused by low-frequency electromagnetic exposure can be used to realize effective medical treatments. However, it is well known that the membrane potential of nerve cells exhibits nonlinearity, particularly in the case of modulated signals, it is important to analyze the nonlinear stimulation effect based on a nerve cell model. This paper adopts the Frankenhaeuser-Huxley (FH) model as the nerve cell model, and evaluates the stimulus response based on the FH model when nerve cells are exposed to low-frequency modulated radio signals such as On-Off Keying (OOK) modulation. This paper investigated the nonlinear effect of the stimulus intensity from the viewpoint of the spike frequency with different modulation parameter values including the induced amplitude and duty cycle. It was confirmed that action potential (AP) rate was higher with OOK-type radio signals than with unmodulated signals.

For an indoor area where a target node is tracked with anchor nodes, we can calculate the priori probability density functions (pdfs) on the distances between the target and anchor nodes by using its shape, three-dimensional sizes and anchor nodes locations. We call it “the area layout information (ALI)” and apply it for two indoor target tracking methods with received signal strength indication (RSSI) assuming a square location estimation area. First, we introduce the ALI to a target tracking method which tracks a target using the weighted sum of its past-to-present locations by a simple infinite impulse response (IIR) low pass filter. Second, we show that the ALI is applicable to a target tracking method with a particle filter where the motion of the target is nonlinearly modelled. The performances of the two tracking methods are evaluated by not only computer simulations but also experiments. The results demonstrate that the use of ALI can successfully improve the location estimation performance of both target tracking methods, without huge increase of computational complexity.

Space diversity reception is well known as a technique that can improve the performance of wireless communication systems without any temporal and spectral resource expansion. Implant body area networks (BANs) require high-speed transmission and low energy consumption. Therefore, applying spatial diversity reception to implant BANs can be expected to fulfill these requirements. For this purpose, this paper presents a local frequency offset diversity system with π/4-differential quadrature phase shift keying (DQPSK) for implant BANs that offer improved communication performance with a simpler receiver structure, and evaluates the proposal's bit error rate (BER) performance by theoretical analysis. In the theoretical analysis, it is difficult to analytically derive the probability density function (pdf) on the combined signal-to-noise power ratio (SNR) at the local offset frequency diversity receiver output. Therefore, this paper adopts the moment generating function approximation method and demonstrates that the resulting theoretical analyses yield performances that basically match the results of computer simulations. We first confirm that the local frequency offset diversity reception can effectively improve the communication performance of implant BANs. Next, we perform an analysis of a realistic communication performance, namely, a link budget analysis based on derived BER performance and evaluate the link parameters including system margin, maximum link distance and required transmit power. These analyses demonstrate that the local frequency offset diversity system can realize a reliable communication link in a realistic implant BAN scenario.

Wireless body area networks (BANs) are attracting great attention as a future technology of wireless networks for healthcare and medical applications. Wireless BANs can generally be divided into two categories, i.e., wearable BANs and implant BANs. However, the performance requirements and channel propagation characteristics of these two kinds of BANs are quite different from each other, that is, wireless signals are approximately transmitted along the human body as a surface wave in wearable BANs, on the other hand, the signals are transmitted through the human tissues in implant BANs. As an effective solution for this problem, this paper first introduces a dual-mode communication system, which is composed of transmitters for in-body and on-body communications and a receiver for both communications. Then, we evaluate the bit error rate (BER) performance of the dual-mode communication system via computer simulations based on realistic channel models, which can reasonably represent the propagation characteristics of on-body and in-body communications. Finally, we conduct a link budget analysis based on the derived BER performances and discuss the link parameters including system margin, maximum link distance, data rate and required transmit power. Our computer simulation results and analysis results demonstrate the feasibility of the dual-mode communication system in wireless BANs.

We conduct, in accordance with IEC 61000-4-2, an electrostatic discharge (ESD) test for a small size battery-operated control circuit board in a myoelectric artificial hand system to investigate the influence of the induced noises by indirect ESDs from an ESD generator to a horizontal coupling plane (HCP) and a vertical coupling plane (VCP). A photo-coupler is set between the small size control board and a motor control circuit to suppress noise in the pulse width modulation (PWM) signals. Two types of ESD noise are observed at the output pins of PWM signals. One type is the ESD noise itself (called Type A) and the other one is the ESD noise superimposed over the PWM pulses (Type B). No matter which polarity the charge voltages of the ESD generator have, both types can be observed and the Type A is dominant in the output pulses. Moreover, the ESD interference in the HCP case is found to be stronger than that in the VCP case usually. In the PWM signals observed at the photo-coupler output, on the other hand, Type A noises tend to increase for positive polarity and decrease for negative polarity, while Type B noises tend to increase at -8kV test level in the HCP case. These results suggest that the photo-coupler does not work well for ESD noise suppression. One of the reasons has been demonstrated to be due to the driving capability of the photo-coupler, and other one is due to the presence of a parasitic capacitance between the input and output of the photo-coupler. The parasitic capacitance can yield a capacitive coupling so that high-frequency ESD noises pass through the photo-coupler.

Wireless capsule endoscopy (WCE) is now one of most important applications in implant body area networks (BANs). WCE requires high throughput performance due to its real-time data transmission, whereas the communication performance depends much on the transmit power, which is strictly regulated in order to satisfy a safety guideline in terms of specific absorption rate (SAR). Spatial diversity reception is well known to improve the wireless performance without any temporal and spectral resource expansion. Additionally, applying spatial diversity reception to WCE systems can be expected to not only improve the wireless communication performance but also to reduce SAR. Therefore, this paper investigates the impact of spatial diversity reception on SAR levels for the 400 MHz medical implant communication service (MICS) band. To begin with, based on finite-difference time-domain (FDTD) simulations for implant BAN propagation with a numerical human body model, we first calculate the BER performance and derive the required transmit power to secure a permissible BER. Then, this paper calculates the local peak SAR under the required transmit power when the implant transmitter moves through the digestive organs. Finally, our simulation results demonstrate that applying spatial diversity reception can significantly reduce SAR in implant BANs.

When using a wireless capsule endoscope (WCE), it is important to know WCE location. In this paper, we focus on a time of arrival (TOA)-based localization technique, as it has better location estimation performance than other radio frequency-based techniques. However, the propagation speed of signals transmitted from inside of a human body varies depending on which biological tissues they pass through. For this reason, almost all of conventional TOA-based methods have to obtain the relative permittivity of the passed biological tissues or the propagation speed beforehand through another measurement system, i.e., magnetic resonance imaging (MRI) or computational tomography (CT). To avoid such troublesome pre-measurement, we propose a hybrid TOA/received signal strength indicator (RSSI)-based method, which can simultaneously estimate the WCE location and the averaged relative permittivity of the human body. First, we derive the principle of RSSI-based relative permittivity estimation from an finite difference time domain (FDTD) simulation. Second, we combine the TOA-based localization and the proposed RSSI-based relative permittivity estimation, and add them to the particle filter tracking technique. Finally, we perform computer simulations to evaluate the estimation accuracy of the proposed method. The simulation results show that the proposed method can accomplish good localization performance, 1.3mm, without pre-measurement of the human body structure information.

In a wireless multi-hop network between a source node (S) and a destination node (D), multipath routing in which S redundantly sends the same packets to D through multiple routes at the same time is effective for enhancing the reliability of the wireless data transmission by means of route diversity. However, when applying the multipath routing to a factory where huge robots are moving around, if closer multiple routes are selected, the probability that they are blocked by the robots at the same time becomes higher, so the reliability in terms of packet loss rate cannot be enhanced. In this paper, we propose a multipath routing method which can select physically distant multiple routes without any knowledge on the locations of nodes. We introduce a single metric composed of “the distance between routes” and “the route quality” by means of scalarization in multi-objective maximization problem and apply a genetic algorithm (GA) for searching for adequate routes which maximize the metric. Computer simulation results show that the proposed method can adaptively control the topologies of selected routes between S and D, and effectively reduce the packet loss rates.

One of promising application offered by implant body area networks (BANs) is a capsule endoscope localization system. To begin with, this paper performs finite-difference time-domain (FDTD) simulations on implant BAN propagation with a numerical human model, and investigates the propagation characteristics of implant BAN signals at 400 MHz medical implant communication service (MICS) band. Then, the paper presents a capsule endoscope localization system which utilizes only received signal strength indicator (RSSI) and two estimation methods, such as a maximum likelihood (ML) estimation method and a least squares (LS) method. Furthermore, we evaluate the two localization methods by two computer simulation scenarios. Our computer simulation results demonstrate that the ML localization can improve the location estimation accuracy as compared with the LS localization, that is, our performance comparison reveals that a careful consideration the propagation characteristics of implant BANs signals is efficient in terms of estimation performance improvement in capsule endoscope localization.

The ability to estimate a target location is essential in many applications of wireless sensor networks. Received signal strength indicator (RSSI)-based maximum likelihood (ML) method in a wireless sensor network usually requires a pre-determined statistical model on the variation of RSSI in a sensing area and uses it as an ML function when estimating the location of a target in the sensing area. However, when estimating the location of a target, due to several reasons, we often measure the RSSIs which do not follow the statistical model, in other words, which are outlier on the statistical model. As the result, the effect of the outlier RSSI data worsens the estimation accuracy. If the wireless sensor network has a lot of sensor nodes, we can improve the estimation accuracy intentionally rejecting such outlier RSSIs. In this paper, we propose a simple outlier RSSI data rejection algorithm for an ML location estimation. The proposed algorithm iteratively eliminates the anchor nodes which measure outlier RSSIs. As compared with the location estimation methods with previously proposed outlier RSSI data rejection algorithms, our proposed method performs better with much less computational complexity.

Tracking capsule endoscope location is one of the promising applications offered by implant body area networks (BANs). When tracking the capsule endoscope location, i.e., continuously localize it, it is effective to take the weighted sum of its past locations to its present location, in other words, to low-pass filter its past locations. Furthermore, creating an exact mathematical model of location transition will improve tracking performance. Therefore, in this paper, we investigate two tracking methods with received signal strength indicator (RSSI)-based localization in order to solve the capsule endoscope location tracking problem. One of the two tracking methods is finite impulse response (FIR) filter-based tracking, which tracks the capsule endoscope location by averaging its past locations. The other one is particle filter-based tracking in order to deal with a nonlinear transition model on the capsule endoscope. However, the particle filter requires that the particle weight is calculated according to its condition (namely, its likelihood value), while the transition model on capsule endoscope location has some model parameters which cannot be estimated from the received wireless signal. Therefore, for the purpose of applying the particle filter to capsule endoscope tracking, this paper makes some modifications in the resampling step of the particle filter algorithm. Our computer simulation results demonstrate that the two tracking methods can improve the performance as compared with the conventional maximum likelihood (ML) localization. Furthermore, we confirm that the particle filter-based tracking outperforms the conventional FIR filter-based tracking by taking the realistic capsule endoscope transition model into consideration.

To improve the performance of capsule endoscope, it is important to add location information to the image data obtained by the capsule endoscope. There is a disadvantage that a lot of existing localization techniques require to measure channel model parameters in advance. To avoid such a troublesome pre-measurement, this paper pays attention to capsule endoscope localization based on an electromagnetic imaging technology which can estimate not only the location but also the internal structure of a human body. However, the electromagnetic imaging with high resolution has huge computational complexity, which should prevent us from carrying out real-time localization. To ensure the accurate real-time localization system without pre-measured model parameters, we apply genetic algorithm (GA) into the electromagnetic imaging-based localization method. Furthermore, we evaluate the proposed GA-based method in terms of the simulation time and the location estimation accuracy compared to the conventional methods. In addition, we show that the proposed GA-based method can perform more accurately than the other conventional methods, and also, much less computational complexity of the proposed method can be accomplished than a greedy algorithm-based method.

This paper aims at channel modeling and bit error rate (BER) performance improvement with diversity reception for in-body to on-body ultra wideband (UWB) communication for capsule endoscope application. The channel characteristics are firstly extracted from 3.4 to 4.8 GHz by using finite difference time domain (FDTD) simulations incorporated with an anatomical human body model, and then a two-path impulse response channel model is proposed. Based on the two-path channel model, a spatial diversity reception technique is applied to improve the communication performance. Since the received signal power at each receiver location follows a lognormal distribution after summing the two path components, we investigate two methods to approximate the lognormal sum distribution in the combined diversity channel. As a result, the method matching a short Gauss-Hermite approximation of the moment generating function (MGF) of the lognormal sum with that of a lognormal distribution exhibits high accuracy and flexibility. With the derived probability density function (PDF) for the combined diversity signals, the average BER performances for impulse-radio (IR) UWB with non-coherent detection are investigated to clarify the diversity effect by both theoretical analysis and computer simulation. The results realize an improvement around 10 dB on Eb/No at BER of 10-3 for two-branch diversity reception.